DESCRIPTION: (Applicant's Abstract) Genetic studies in animal models rely primarily on mice. Studies on glaucoma require measurement of intraocular pressure (IOP) which is very difficult in mice. The goal of this NEI R03 proposal is to develop a standardized, non-invasive method for measuring IOP in mice. To achieve this goal, we will modify, test and validate an induction-driven impact (1/1) tonometry method. A tonometer based on this method is simple, can be made with relatively inexpensive components, and should provide reliable data for repeated measurements over extended time periods. It will allow for repetitive measurement of IOP without affecting ocular physiology. To refine the 1/1 method specifically for use in mouse IOP measurement, we will conduct experiments manipulating the following variables: mass and design of the probe, probe magnetization, coil characteristics and probe speed. We will also optimize the software algorithm that uses probe movement parameters to determine IOP. The validity, accuracy and reliability of IOP measurement will be tested against manometric IOP determinations. Next, to demonstrate utility, it will be used to monitor IOP at 2-monthly intervals up to I year of age, in several strains of inbred mice commonly used for genetic experiments. The ability of the I/I method to track the age-dependent increase in IOP in the closed-angle type of glaucoma that develops spontaneously in two substrains of the DBA/2 mouse will be tested. Finally, because glaucoma is a disease affecting retinal ganglion cells and their axons, we will assess the correlation between IOP measurements obtained with the III method and the changes in number and pattern of RGC distribution in DBA/2 mice, adapting a method that has been previously developed in our laboratory for accurately quantifying ganglion cells in the rat retina that has no sampling bias. Successful completion of this pilot project will create a platform for further research in understanding the pathogenesis of glaucoma using mice as models and will provide high throughput methods that can be used for genetic and other studies.